diff options
Diffstat (limited to 'src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp')
| -rw-r--r-- | src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp | 102 |
1 files changed, 102 insertions, 0 deletions
diff --git a/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp b/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp new file mode 100644 index 0000000000..5a2939b587 --- /dev/null +++ b/src/cpu/kernels/boundingboxtransform/generic/neon/impl.cpp @@ -0,0 +1,102 @@ +/* + * Copyright (c) 2019-2023 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "src/cpu/kernels/boundingboxtransform/generic/neon/impl.h" + +#include "src/cpu/CpuTypes.h" + +namespace arm_compute +{ +namespace cpu +{ +void bounding_box_transform_qsymm16(const ITensor *boxes, + ITensor *pred_boxes, + const ITensor *deltas, + BoundingBoxTransformInfo bbinfo, + const Window &window) + +{ + const size_t num_classes = deltas->info()->tensor_shape()[0] >> 2; + const size_t deltas_width = deltas->info()->tensor_shape()[0]; + const int img_h = std::floor(bbinfo.img_height() / bbinfo.scale() + 0.5f); + const int img_w = std::floor(bbinfo.img_width() / bbinfo.scale() + 0.5f); + + const auto scale_after = (bbinfo.apply_scale() ? bbinfo.scale() : 1.f); + const auto scale_before = bbinfo.scale(); + const auto offset = (bbinfo.correct_transform_coords() ? 1.f : 0.f); + + auto pred_ptr = + reinterpret_cast<uint16_t *>(pred_boxes->buffer() + pred_boxes->info()->offset_first_element_in_bytes()); + auto delta_ptr = reinterpret_cast<uint8_t *>(deltas->buffer() + deltas->info()->offset_first_element_in_bytes()); + + const auto boxes_qinfo = boxes->info()->quantization_info().uniform(); + const auto deltas_qinfo = deltas->info()->quantization_info().uniform(); + const auto pred_qinfo = pred_boxes->info()->quantization_info().uniform(); + + Iterator box_it(boxes, window); + execute_window_loop( + window, + [&](const Coordinates &id) + { + const auto ptr = reinterpret_cast<uint16_t *>(box_it.ptr()); + const auto b0 = dequantize_qasymm16(*ptr, boxes_qinfo); + const auto b1 = dequantize_qasymm16(*(ptr + 1), boxes_qinfo); + const auto b2 = dequantize_qasymm16(*(ptr + 2), boxes_qinfo); + const auto b3 = dequantize_qasymm16(*(ptr + 3), boxes_qinfo); + const float width = (b2 / scale_before) - (b0 / scale_before) + 1.f; + const float height = (b3 / scale_before) - (b1 / scale_before) + 1.f; + const float ctr_x = (b0 / scale_before) + 0.5f * width; + const float ctr_y = (b1 / scale_before) + 0.5f * height; + for (size_t j = 0; j < num_classes; ++j) + { + // Extract deltas + const size_t delta_id = id.y() * deltas_width + 4u * j; + const float dx = dequantize_qasymm8(delta_ptr[delta_id], deltas_qinfo) / bbinfo.weights()[0]; + const float dy = dequantize_qasymm8(delta_ptr[delta_id + 1], deltas_qinfo) / bbinfo.weights()[1]; + float dw = dequantize_qasymm8(delta_ptr[delta_id + 2], deltas_qinfo) / bbinfo.weights()[2]; + float dh = dequantize_qasymm8(delta_ptr[delta_id + 3], deltas_qinfo) / bbinfo.weights()[3]; + // Clip dw and dh + dw = std::min(dw, bbinfo.bbox_xform_clip()); + dh = std::min(dh, bbinfo.bbox_xform_clip()); + // Determine the predictions + const float pred_ctr_x = dx * width + ctr_x; + const float pred_ctr_y = dy * height + ctr_y; + const float pred_w = std::exp(dw) * width; + const float pred_h = std::exp(dh) * height; + // Store the prediction into the output tensor + pred_ptr[delta_id] = quantize_qasymm16( + scale_after * utility::clamp<float>(pred_ctr_x - 0.5f * pred_w, 0.f, img_w - 1.f), pred_qinfo); + pred_ptr[delta_id + 1] = quantize_qasymm16( + scale_after * utility::clamp<float>(pred_ctr_y - 0.5f * pred_h, 0.f, img_h - 1.f), pred_qinfo); + pred_ptr[delta_id + 2] = quantize_qasymm16( + scale_after * utility::clamp<float>(pred_ctr_x + 0.5f * pred_w - offset, 0.f, img_w - 1.f), + pred_qinfo); + pred_ptr[delta_id + 3] = quantize_qasymm16( + scale_after * utility::clamp<float>(pred_ctr_y + 0.5f * pred_h - offset, 0.f, img_h - 1.f), + pred_qinfo); + } + }, + box_it); +} +} // namespace cpu +} // namespace arm_compute |